BGVAR
Bayesian Global Vector Autoregressions
Estimation of Bayesian Global Vector Autoregressions (BGVAR) with different prior setups and the possibility to introduce stochastic volatility. Built-in priors include the Minnesota, the stochastic search variable selection and Normal-Gamma (NG) prior. For a reference see also Crespo Cuaresma, J., Feldkircher, M. and F. Huber (2016) "Forecasting with Global Vector Autoregressive Models: a Bayesian Approach", Journal of Applied Econometrics, Vol. 31(7), pp. 1371-1391
- Version2.5.5
- R version≥ 3.5.0
- LicenseGPL-3
- Needs compilation?Yes
- Languageen-US
- Last release12/13/2023
Documentation
Team
Maximilian Boeck
Martin Feldkircher
Florian Huber
Darjus Hosszejni
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Dependencies
- Depends1 package
- Imports18 packages
- Suggests2 packages
- Linking To6 packages